# Tunables for frank-default-large (kingjones777 Qwen3.8-Flash-Next
# ROCmFP4 STRIX_LEAN, qwen4exp hybrid MoE, Dankclaw, Strix Halo gfx1151).
#
# Runtime: ROCmFPX llama.cpp fork with PR #27742 (qwen4exp architecture)
# merged and built at /home/dank/GitPackages/ROCmFPX/build-qwen38.
# Build flags: -DGGML_HIP=ON -DGGML_HIP_ROCMI4_W4A4=ON
# -DCMAKE_HIP_ARCHITECTURES=gfx1151 -DGGML_CUDA_FA_ALL_QUANTS=ON
# -DLLAMA_BUILD_WEBUI=OFF -DCMAKE_EXE_LINKER_FLAGS=-no-pie.
# Replaced the kingjones Qwen3.8-27B Q6_0 AGENT deployment on 2026-09-01.
#
# Model: kingjones777/Qwen3.8-Flash-Next-ROCmFP4-STRIX_LEAN-GGUF.
# 56B MoE (512 experts, 10 used), 48 layers (12 attention + 36 SSM,
# full_attention_interval=4), 2 KV heads × 256 dim, embedding 2560,
# QSA indexer (4 heads, key_length 128, top_k 2048), hyper-connections
# (count=4, low_rank=320), PLE (layer 1, ngram_size=3, heads_per_ngram=8).
# Q4_0_ROCMFP4_STRIX_LEAN quant, 98.5 GiB, 3-part GGUF split.
# Text-only (no mmproj, no MTP draft head).
#
# Context: 262144 (256k) × 2 slots.  f16 KV cache (~6.4 GiB per slot,
# ~12.8 GiB total).  --fit off because the auto-fit code segfaults on this
# model's hyper-connection/indexer config; -ngl 999 places all layers on
# the SVM-backed GPU pool (116 GiB unified).
#
# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE. The
# ROCm HIP runtime reads those bare env vars (see the 2026-08-13 TEMP
# incident). llama.cpp reads --host/--port/--temp as CLI flags, never as
# env vars.

# ROCmFPX llama-server (PR #27742 merged, build-qwen38).
LLAMA_BIN=/home/dank/GitPackages/ROCmFPX/build-qwen38/bin/llama-server

# Model files from
# https://huggingface.co/kingjones777/Qwen3.8-Flash-Next-ROCmFP4-STRIX_LEAN-GGUF
MODEL_DIR=/home/dank/models/kingjones-Qwen3.8-Flash-Next-ROCmFP4-STRIX_LEAN
MODEL_FILE=Qwen3.8-Flash-Next-ROCmFP4-STRIX_LEAN-00001-of-00003.gguf

# Qwen-Sharp chat template (tracked in the repo, staged on the host). The
# Sharp template drives thinking on by default (medium effort); the server
# emits reasoning in DeepSeek format so clients receive reasoning_content
# separately instead of literal thinking tags in content.
CHAT_TEMPLATE_FILE=/home/dank/serverAppConfigs/scripts/chat-template.jinja
CHAT_TEMPLATE_KWARGS='{"enable_thinking":true,"preserve_thinking":true,"preserve_reasoning":true}'

# Alias + network.
ALIAS=frank-default-large
BIND_ADDR=0.0.0.0
LISTEN_PORT=7770

# Serving: 262144 context (256k) × 2 slots. f16 KV, context checkpoints,
# prompt cache. The model is 98.5 GiB loaded via mmap into the Strix Halo
# unified memory pool (116 GiB SVM-backed). --fit off avoids the auto-fit
# segfault on this model's qwen4exp hyper-connection/indexer configuration.
CTX_SIZE=524288
PARALLEL=2
BATCH_SIZE=4096
UBATCH_SIZE=4096
NUM_THREADS=16
THREAD_BATCH=32
CACHE_TYPE_K=f16
CACHE_TYPE_V=f16
CTX_CHECKPOINTS=16
CACHE_RAM=8192
FIT=off

# Sampling (Sharp default).
TEMPERATURE=0.7
TOP_K=20
TOP_P=0.8
MIN_P=0.0
PRESENCE_PENALTY=1.5

# Reasoning on (Sharp template drives it; preserve_thinking + preserve_reasoning
# keep the reasoning trail in the conversation). DeepSeek format projects the
# reasoning into the API's reasoning_content field instead of content tags.
REASONING=on
REASONING_FORMAT=deepseek

# Strix Halo unified memory + native gfx1151.
HSA_OVERRIDE_GFX_VERSION=11.5.1

VERBOSITY=4